Ion beam paths on target surfaces for neutron beam generation

ABSTRACT

Embodiments of systems, devices, and methods relate to selecting a raster profile for scanning a proton beam across a target. A raster profile is selected from among the plurality of plurality of possible raster profiles based on a value of a figure of merit. A beam is directed across the target surface to form a pattern that is repeated one or more times at different radial orientations to form a scanning profile. A target temperature is monitored while scanning the beam across the target surface according to the scanning profile. The scanning parameters are changeable to avoid target damaging, to improve thermal performance and to optimize particle loading.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority under 35 U.S.C. 119 to ProvisionalApplication No. 63/070,789, filed Aug. 26, 2020, which is incorporatedby reference.

FIELD

The subject matter described herein relates generally to systems,devices, and methods for determining and directing an ion beam path on atarget surface, and more particularly determining and directing an ionbeam path on a target surface for neutron beam generation.

BACKGROUND

Boron neutron capture therapy (BNCT) is a modality of treatment of avariety of types of cancer, including some of the most difficult types.BNCT is a technique that selectively aims to treat tumor cells whilesparing the normal cells using a boron compound. The boron compoundallows for efficient uptake by a variety of cell types and selectivedrug accumulation at target sites, such as tumor cells. Boron loadedcells can be irradiated with neutrons (e.g., in the form of a neutronbeam). The neutrons react with the boron to eradicate the tumor cells.

Neutron beams for BNCT can be generated by irradiating a suitable targetwith an ion beam, such as a proton beam. The ions react with nuclei inthe target to emit a beam of neutrons that can be used for BNCT.Exposure of a target to an ion beam for a prolonged period can result indegradation of the target and the resulting neutron beam. Targets can bereplaced but may be expensive and result in system down time.Accordingly, a need exists for improved proton beam delivery to prolonga target's functionality below a temperature limit and reduce systemdown time.

SUMMARY

Example embodiments of systems, devices, and methods described hereinrelate to a selection of a profile for scanning an ion beam (e.g., aproton beam) across a target surface. In some implementations, a beampath across the target surface forms a first pattern. The pattern, alsocalled a fundamental pattern or cycle, is repeated one or more times atdifferent radial orientations from the first instance of the pattern toform a scanning profile. Here, a “radial” orientation refers to anazimuthal or, alternatively, circumferential direction in a cylindricalcoordinate system. The embodiments include at least two instances of afirst beam pattern radially offset from each other. The variousinstances of the beam pattern can be offset by a constant amount suchthat the scanning profile includes instances of the pattern clocked atregular radial intervals. The embodiments are based on computationalmodelling configured to improve thermal performance and particleloading, among other advantages. For example, computational modellingcan allow for selection of beam scan (or raster) profiles that improveuniformity of particle loading on a target and/or can allow selection ofa scanning profile that reduces (e.g., minimizes) peak transienttemperature of the target. The computational model indicates the thermaleffect on a target of several beam parameters, such as the beam's sizeand shape. The computational model can include a meshed spaceencompassing the target. The mesh is composed of a three-dimensionalgrid in which the thermal loads on the target are modeled. Thetemperature values are obtained by solving a one-dimensional heattransport equation at each “pixel” (element) of the grid. Theone-dimensional heat transport equation is solved for thermal transportthrough the depth of the pixel considering that cross talk betweenpixels or lateral heat conduction between pixels is assumed to benegligible. Numerical approaches used to solve the one-dimensional heattransport differential equation include finite-element andfinite-difference methods. For either of the finite-element andfinite-difference techniques, the target is represented in a plan viewas a portion of a grid. The grid can have the same unit cell size ineach dimension or the size in each dimension can differ. Resolution canbe selected to provide the ability to model beams of different size andstructure in line to the physical capabilities of the system understudy. The computational model enables selection of a scan profile thatdefines a path for the proton beam having a minimum delay betweensuccessive exposures of a single location of the target to the protonbeam exceeds a threshold period. The selected profile can define a pathbased on a trochoid shape including a plurality of lobes. Thecomputational model enables a selection of a profile that has a varyingangular frequency of the proton beam between different lobes of thetrochoid shape. The computational model enables a selection of a profilethat has a varying angular velocity of the proton beam across the targetsurface. The computational model enables a selection of a scan profilethat has a varying linear velocity of the proton beam across the targetsurface.

In one aspect, this document describes a method of scanning the beamacross a scannable surface of a target along a first path, and scanningthe beam across the scannable surface of the target along a second path,wherein the first path forms a first pattern at a first radialorientation, and the second path forms substantially the first patternat a second radial orientation different from the first radialorientation. The beam can be pulsed while scanning along the first andsecond paths. The beam continuously propagates while scanning along thefirst and second paths. The beam moves from an inner region to an outerregion of the scannable surface and back to the inner region in thefirst pattern. The beam moves from an outer region to an inner region ofthe scannable surface and back to the outer region in the first pattern.The first pattern can include a spiral and a mirror image of the spiral.The first pattern has a first half and a second half, wherein the firstand second halves are symmetrical. The first pattern can be continuouslycurved. The first pattern has a start location and a stop location,wherein the start location can be at or adjacent to the stop location.The first radial orientation differs from the second radial orientationby 180 degrees. The operations can further include: scanning the beamacross the scannable surface of the target along a third path, whereinthe third path forms the first pattern at a third radial orientationdifferent from the first and second radial orientations. The first,second, and third radial orientations differ by 120 degrees. Theoperations can further include: scanning the beam across the scannablesurface of the target along a fourth path, wherein the fourth path formsthe first pattern at a fourth radial orientation different from thefirst, second, and third radial orientations. The first, second, third,and fourth radial orientations differ by 90 degrees. The operations canfurther include: scanning the beam across the scannable surface of thetarget along a fifth path, wherein the fifth path forms the firstpattern at a fifth radial orientation different from the first, second,third, and fourth radial orientations. The first, second, third, fourth,and fifth radial orientations differ by 72 degrees. The first pathcorresponds to a first instance of a cycle, and the second pathcorresponds to a second instance of the cycle. In some implementations,scanning of the first instance of the cycle and the second instance ofthe cycle forms a closed loop. The beam can be a proton beam. Thescannable surface can be a lithium or beryllium surface. The targetgenerates neutrons when scanned. The beam has a circular cross-sectionalprofile. The beam has an elliptical cross-sectional profile. The beamhas an annular cross-sectional profile. The beam has a hollowcross-sectional profile. The operations performing a boron neutroncapture therapy (BNCT). The beam can be generated by a beam systemincluding: an ion source, a first beamline coupled with the ion source,a tandem accelerator coupled with the first beamline, a second beamlinecoupled with the tandem accelerator, and the target coupled with thesecond beamline. The pattern exposes a majority of the scannable surfaceto the beam. The second path forms the first pattern at the secondradial orientation different from the first radial orientation.

In another aspect, this document describes a method of operating a beam,including: scanning the beam across a scannable surface of a targetalong a first path, and scanning the beam across the scannable surfaceof the target along a second path, wherein the first path forms a firstpattern at a first radial orientation, and the second path forms asecond pattern at a second radial orientation different from the firstradial orientation, wherein the first and second patterns aresubstantially the same but for the different radial orientations. Thefirst and second patterns are the same but for the different radialorientations.

In another aspect, this document describes a beam system including: acomputing device including a processor communicatively coupled withmemory, wherein the memory stores a plurality of instructions that, whenexecuted by the processor, cause the processor to: control movement of abeam across a scannable surface of a target along a first path, andcontrol movement of the beam across the scannable surface of the targetalong a second path, wherein the first path can include a first patternat a first radial orientation, and the second path can includesubstantially the first pattern at a second radial orientation differentfrom the first radial orientation. The first path traverses from aninner region to an outer region of the scannable surface and back to theinner region in the first pattern. The first path traverses from anouter region to an inner region of the scannable surface and back to theouter region in the first pattern. The first pattern can include aspiral and a mirror image of the spiral. The first pattern can include afirst half and a second half, wherein the first and second halves aresymmetrical. The first pattern can be continuously curved. The firstpattern can include a start location and a stop location, wherein thestart location can be at or adjacent to the stop location. The firstradial orientation differs from the second radial orientation by 180degrees. The plurality of instructions, when executed by the processor,further cause the processor to: control movement of the beam across thescannable surface of the target along a third path, wherein the thirdpath can include the first pattern at a third radial orientationdifferent from the first and second radial orientations. The first,second, and third radial orientations differ by 120 degrees. Theplurality of instructions, when executed by the processor, further causethe processor to: control movement of the beam across the scannablesurface of the target along a fourth path, wherein the fourth path caninclude the first pattern at a fourth radial orientation different fromthe first, second, and third radial orientations. The first, second,third, and fourth radial orientations differ by 90 degrees. The systemplurality of instructions, when executed by the processor, further causethe processor to: control movement of the beam across the scannablesurface of the target along a fifth path, wherein the fifth path caninclude the first pattern at a fifth radial orientation different fromthe first, second, third, and fourth radial orientations. The first,second, third, fourth, and fifth radial orientations differ by 72degrees. The plurality of instructions, when executed by the processor,further cause the processor to: control movement of the beam across thescannable surface of the target along a sixth path, wherein the sixthpath can include the first pattern at a sixth radial orientationdifferent from the first, second, third, fourth, and fifth radialorientations. The first, second, third, fourth, fifth, and sixth radialorientations differ by 60 degrees. The beam can be a proton beam. Thescannable surface can be a surface of a lithium layer or berylliumlayer. The target generates neutrons when scanned. The beam can includea circular profile. The beam can include an elliptical profile. The beamcan include an annular profile. The beam can include a hollow profile.The operations are performed in boron neutron capture therapy (BNCT).The beam can be generated by a beam system including: an ion source, afirst beamline coupled with the ion source, a tandem accelerator coupledwith the first beamline, a second beamline coupled with the tandemaccelerator, and the target coupled with the second beamline. The firstpattern exposes a majority of the scannable surface to the beam. Thesecond path forms the first pattern at the second radial orientationdifferent from the first radial orientation.

In another aspect, this document describes a computer-implemented methodfor selecting a raster profile for scanning a proton beam across atarget, the method including: establishing, using a computer processingsystem, a plurality of possible raster profiles for scanning the protonbeam across the target, each of the plurality of possible rasterprofiles including one or more beam parameters, each of the one or morebeam parameters characterizing a property of the proton beam and one ormore path parameters characterizing a path of the proton beam across thetarget, establishing, using the computer processing system, one or moretarget parameters characterizing the target, calculating, using thecomputer processing system, a value of a figure of merit for each of thepossible beam raster profiles, wherein the figure of merit can be basedon a thermal loading of the target by the proton beam for thecorresponding possible raster profile, selecting, using the computerprocessing system, a raster profile from among the plurality ofplurality of possible raster profiles based on the value of the figureof merit, and directing the proton beam across the target according tothe selected raster profile. Calculating the values for the figure ofmerit can include, for each of the possible raster profiles, calculatinga thermal load at each of a plurality of discrete portions of the targetbased on a linear relationship between the thermal load and a protonflux at each discrete portion for the corresponding raster profile. Eachdiscrete portion corresponds to an area of a surface of the target inthe path of the proton beam that can be smaller than a dimension of theproton beam. The thermal load at each discrete portion can be calculatedbased on heat transfer through a depth of the target away from a surfaceof the target on which the proton beam can be incident. The figure ofmerit can be selected from the group consisting of: a peak temperatureof the target, a temperature change of the target, an averagetemperature of the target, and a usage efficiency of the target. The oneor more beam parameters are selected from the group consisting of: abeam dimension, a beam shape, and a beam structure. The beam dimensioncan be in a range from 10 mm to 30 mm. The beam shape can be circular orelliptical. A structure of the beam can be circular or annular. The oneor more path parameters can be selected from the group consisting of: afrequency associated with the path of the proton beam, a linear velocityof the proton beam across a surface of the target, a number of radialscan layers in a super cycle of the path of the proton beam, and anumber of super cycles of the path of the proton beam. The one or moretarget parameters are selected from the group consisting of: targetsurface area, target thickness, and target composition. The target caninclude a layer of lithium or a layer of beryllium. The target caninclude a layer of a metal supporting the layer of lithium or the layerof beryllium. Selecting can include presenting an operator of the protonbeam with a list of the possible raster profiles and receiving, via thecomputer system, a selection from the list by the operator. Theoperations can further include measuring one or more properties of thetarget and selecting the raster profile based on the measured propertyof the target. The one or more properties of the target comprise atemperature of the target at one or more locations on the target. Theoperations, can further include measuring one or more properties of thebeam and selecting the raster profile based on the measured property ofthe beam. The one or more properties of the beam are measured upstreamfrom the target. The selected raster profile defines a path for theproton beam having a minimum delay between successive exposures of asingle location of the target to the proton beam exceeds a thresholdperiod. The selected raster profile defines a path based on a trochoidshape. The trochoid shape can include a plurality of lobes. The angularfrequency of the proton beam varies for different lobes of the trochoidshape. The selected raster profile can include a varying angularvelocity of the proton beam across the target surface. The selectedraster profile can include a varying linear velocity of the proton beamacross the target surface.

In another aspect, this document describes a computer-implemented methodincluding: monitoring a temperature of a target while scanning a protonbeam across a surface of the target according to a first raster profile,and based on the monitored temperature, changing the scanning from thefirst raster profile to a second raster profile, wherein the secondraster profile and the first raster profile result in differing heatingprofiles of the target according to a computer model of a thermalloading of the target by the first and second raster profiles. Thescanning can be changed in response to selection of the second rasterprofile from among a plurality of raster profiles by a human operator ofthe proton beam. The scanning can be changed automatically according toa feedback or feedforward algorithm. The temperature can be monitored atmultiple discrete locations of the target. The temperature can bemonitored by obtaining a thermal image of the target.

In another aspect, this document describes a method of operating a beam,including scanning a charged particle beam across a scannable surface ofa target in a super cycle, wherein the super cycle can include aplurality of cycles, each cycle of the plurality of cycles having thesame shape and a different azimuthal orientation, wherein the pluralityof cycles are concatenated together such that a path of the chargedparticle beam traverses the plurality of cycles in a closed loop. Theplurality of cycles can include two cycles azimuthally offset by 180degrees from each other. The plurality of cycles can include threecycles azimuthally offset by 120 degrees from each other. The pluralityof cycles can include four cycles azimuthally offset by 90 degrees fromeach other.

Other systems, devices, methods, features and advantages of the subjectmatter described herein will be or will become apparent to one withskill in the art upon examination of the following figures and detaileddescription. It is intended that all such additional systems, methods,features and advantages be included within this description, be withinthe scope of the subject matter described herein and be protected by theaccompanying claims. In no way should the features of the exampleembodiments be construed as limiting the appended claims, absent expressrecitation of those features in the claims.

BRIEF DESCRIPTION OF DRAWINGS

The details of the subject matter set forth herein, both as to itsstructure and operation, may be apparent by study of the accompanyingfigures, in which like reference numerals refer to like parts. Thecomponents in the figures are not necessarily to scale, emphasis insteadbeing placed upon illustrating the principles of the subject matter.Moreover, all illustrations are intended to convey concepts, whererelative sizes, shapes and other detailed attributes may be illustratedschematically rather than literally or precisely.

FIG. 1A is a schematic view of an example embodiment of a neutron beamsystem in accordance with the present disclosure.

FIG. 1B is a schematic view of an example embodiment of a neutron beamsystem for use in boron neutron capture therapy (BNCT).

FIG. 2A is a perspective view of an example embodiment of a target.

FIG. 2B is a cross-sectional view taken along line 2B-2B of FIG. 2A.

FIG. 2C is a cross-sectional view of another example embodiment of atarget.

FIG. 3A is a schematic view of an example of a beam path that forms afirst pattern in accordance with the present subject matter.

FIGS. 3B-3C are schematic views of example beam paths with ellipticaland circular beam cross-sectional profiles, respectively.

FIGS. 4A-4G are example embodiments of scanning profiles having multipleinstances of a beam pattern repeated at different radial orientations.

FIGS. 5A and 5B are examples of computer models including a target inaccordance with the present disclosure.

FIGS. 6A-6D are examples of modeled thermal maps in accordance with thepresent disclosure.

FIGS. 7A-7F are examples of recent path avoidance (RPA) patterns.

FIGS. 8A and 8B are examples of simulated boundary temperature and usagemaps.

FIGS. 9A-9J are examples of simulation results in accordance withimplementations of the present disclosure.

FIG. 10 is a flowchart depicting an example process that can be executedin accordance with implementations of the present disclosure.

FIG. 11 is an example system that can be implemented in accordance withthe present disclosure.

FIG. 12 is a schematic illustration of example computer systems that canbe used to execute implementations of the present disclosure.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

Before the present subject matter is described in detail, it is to beunderstood that this disclosure is not limited to the particularembodiments described, as such may, of course, vary. It is also to beunderstood that the terminology used herein is for the purpose ofdescribing particular embodiments only, and is not intended to belimiting, since the scope of the present disclosure will be limited onlyby the appended claims.

The term “particle” is used broadly herein and, unless otherwiselimited, can be used to describe an electron, a proton (or H+ ion), or aneutron, as well as a species having more than one electron, proton,and/or neutron (e.g., other ions, atoms, and molecules).

Example embodiments of systems, devices, and methods are describedherein for beam paths of a beam along a target surface of, or used incombination with, a beam system (e.g., including a particleaccelerator). The embodiments described herein can be used with any typeof particle accelerator or in any particle accelerator applicationinvolving production of a charged particle beam at specified energiesfor supply to the particle accelerator. Embodiments herein can be usedin numerous applications, an example of which is as a neutron beamsystem for generation of a neutron beam for use in boron neutron capturetherapy (BNCT). BNCT uses a beam of epithermal neutrons (e.g., with anenergy spectrum within 3-30 kiloelectronvolts) for cancer treatment. Insome implementations, the epithermal neutrons (e.g., epithermal neutronbeams) are generated based on nuclear reactions of protons (e.g., aproton beam) with either a Beryllium target or a Lithium target.

The proton beam can be generated by a particle accelerator, such as atandem accelerator. For example, the tandem accelerator can be anelectrostatic accelerator that employs a two-step acceleration ofcharged particles using a single high voltage terminal. The high voltagecan be used to generate an electric field that is applied to theincoming beam of negatively charged ions to accelerate it towards thecenter of the accelerator. The center of the tandem accelerator can beconfigured to convert the beam of negatively charged ions into a protonbeam in a process of charge exchange. The parameters of the proton beam,such as a beam dimension, a beam shape, and a beam structure can bevaried to optimize target usage relative to localized heating of thetarget.

For ease of description, many embodiments described herein will be doneso in the context of scanning a proton beam across a target to generatea neutron beam for use in BNCT, although the embodiments are not limitedto such, and can be applied to scanning of other charged particle beams,generation of beams other than neutron beams, and usages outside of BNCTapplications. The target can be maintained in a fixed (unvarying)position while scanning the proton beam across the target surface.Alternatively, the target can be moved (e.g., rotated) while the protonbeam is scanned across the target surface. Both approaches are describedherein. The embodiments pertaining to the scanning (rastering) ofcharged particle beams are described primarily in the context of a fixedtarget; however all such embodiments can be configured for use in theapproach where the target is moving.

FIG. 1A illustrates a schematic view of an example embodiment of asystem 100 for use in BNCT, in accordance with the present disclosure.The system 100 includes a beam system 102 configured to generate aproton beam 104 and a target 196 that is scanned by the proton beam 104to generate a neutron beam 106 that is directed towards a patient 108.The beam system 102 includes a charged particle source 122, a low-energybeamline (LEBL) 190, an accelerator 140 and a high-energy beamline(HEBL) 150. The accelerator 140 is coupled to the low-energy beamline(LEBL) 190 and is configured to accelerate a charged particle (proton)beam. The high-energy beamline (HEBL) 150 extends from the accelerator140 to a target assembly 110 housing a target 196 onto which the chargedparticle beam can be directed. LEBL 190 is configured to transport thebeam from source 122 to the accelerator 140. The accelerator 140 isconfigured to accelerate the beam HEBL 150 transfers the beam 104 froman output of accelerator 140 to the target 196. In some implementations,the HEBL 150 transfers the beam 104 to the target 196 through a targetchamber of the target assembly 110. The beam 104 can be a negativecharged particle beam or a positive charge particle beam. The target 196can be a device that converts the charged particle beam 104 into anothertype of particle beam 106, such as a neutral beam, can be a workpiece,or other body onto which the charge particle beam is directed for usefulpurpose, such as an irradiating target of a patient 108.

FIG. 1B is a schematic view illustrating an example embodiment of thebeam system 102 configured as a neutron beam system for use in BNCT. Thebeam system 102 includes a pre-accelerator system 120 forming at least aportion of the LEBL, where the pre-accelerator system 120 serves as acharged particle beam injector, a high voltage (HV) tandem accelerator140 coupled to the pre-accelerator system 120, and a high-energybeamline 150 extending from the HV tandem accelerator 140 to a neutrontarget assembly 110 housing a neutron-producing target 196, as describedwith reference to FIG. 1A. The beam system 102 as well aspre-accelerator system 120 can also be used for other applications, suchas cargo inspection and applications, and is not limited to BNCT.

The pre-accelerator system 120 (also referred to herein as the chargedparticle beam injector or ion beam injector) can be configured totransfer the ion beam from an ion source 122 to an input (e.g., an inputaperture) of the HV tandem accelerator 140. The pre-accelerator system120 can include the ion source 122 (e.g., negative ion source), aturbomolecular pump 124 (e.g., an ion source vacuum chamber for removinggas), a pre-acceleration tube 126, and a pump chamber 128. In someimplementations, the beam source 122 can include a negative ion source.The pre-accelerator system 120 can be configured to provide accelerationof the beam particles to energy levels required for the HV tandemaccelerator 140, and to provide an overall convergence of the negativeion beam to match an input aperture area at an input aperture orentrance of the HV tandem accelerator 140. The pre-accelerator system120 can be configured to minimize or defocus backflow as it passes fromthe HV tandem accelerator 140 through the pre-accelerator system 120 inorder to reduce the possibility of damage to ion source 122 and/or thebackflow reaching the filaments of the ion source 122.

The HV tandem accelerator 140 is powered by a high voltage power supply142 coupled thereto. The HV tandem accelerator 140 includes a vacuumtank, a charge-exchange target, accelerating electrodes, and a highvoltage feedthrough. The HV tandem accelerator 140 can, in someimplementations, accelerate a hydrogen beam to produce a proton beamwith an energy generally equal to twice the voltage applied to theaccelerating electrodes positioned within the HV tandem accelerator 140.The energy level of the proton beam can be achieved by accelerating thebeam of negative hydrogen ions from the input of the HV tandemaccelerator 140 to the innermost high-potential electrode, stripping twoelectrons from each ion, and then accelerating the resulting protonsdownstream by the same voltages encountered in reverse order.

The high-energy beamline 150 can transfer the proton beam from theoutput of the HV tandem accelerator 140 to the neutron-generating target196 in the neutron target assembly 110 positioned at the end of a branch170 of the beamline extending into a patient treatment room.

The beam system 102 can be configured to direct the proton beam to oneor more targets 196 and associated target areas. In someimplementations, the high-energy beamline 150 includes multiple (e.g.,three) branches 170, 180, and 190 configured to extend to multipledifferent patient treatment rooms. The branches 180 and 190 can containtarget assemblies similar to branch 170. The high-energy beamline 150includes a pumping chamber 151, quadrupole magnets 152 and 172 toprevent de-focusing of the beam, dipole or bending magnets 156 and 158to steer the beam towards one or more targets, beam correctors 153,diagnostics such as current monitors 154 and 176, fast beam positionmonitor 155 section, and a scanning magnet 174.

The beam system 102 may employ one or more control systems 1101 withwhich one or more computing devices 1102 may communicate in order tointeract with the systems and components of the beam system 102 (e.g.,neutron beam system 102). In some implementations, the computing device1102 is configured to execute a computational model that enablesselection of a raster profile, as described with reference to FIGS. 5Aand 5B. The computing device 1102 is configured to receive a user inputincluding a selection of one or more parameters of the target scanningprocess. The parameters can define the raster profile including the beampath, the orientation of a shaped beam relative to the scannable surfaceof the target, the beam cross-sectional profile, and the beam velocity.The parameters can define target characteristics, such as rotation ofthe target 196 (e.g., angular velocity of the target). The raster pathas used herein does not imply any particular beam path (e.g., such asmoving only in orthogonal directions). In some implementations, thecomputing devices 1102 are configured to receive a real time signalmeasured by a sensor 121 or a thermal camera 123, which are used toadjust in real time the raster profile using an adaptable scanningprogram to avoid local overheating of the target 196 (e.g., keeping thelocal temperature below Lithium melting temperature of 180° C.). The oneor more thermal sensors 121 can detect localized temperaturecorresponding to a portion of the target. The thermal camera 123 can beconfigured to generate a signal that can be processed to generate atemperature map of the target 196. The computing device 1102 can beconfigured to process the received input and generate a set of scanningparameters that are transmitted to the one or more control systems 1101to control the target scanning process.

The design of the high-energy beamline 150 depends on the configurationof the treatment facility (e.g., a single-story configuration of atreatment facility, a two-story configuration of a treatment facility,and the like). The beam can be delivered to a target assembly 110 (e.g.,positioned near a treatment room having a patient 108) with the use ofthe bending magnet 156. Quadrupole magnets 172 can be included to thenfocus the beam to a certain size at the target. The beam can pass one ormore scanning magnets 174, which provide lateral movement of the beamonto the target surface in a desired pattern (e.g., spiral, curved,stepped in rows and columns, combinations thereof, and others). The beamlateral movement can enable generation of smooth and even time-averageddistribution of the proton beam on the target 196, preventingoverheating of the target 196 and making the particle (e.g., neutron)generation as uniform as possible within the target layer 201 (e.g.,lithium layer).

The scanning magnets 174 can be configured to direct the beam to acurrent monitor 176, which measures beam current. The beam currentvalue, measured by the current monitor 176, can be used to operate asafety interlock. The target assembly 110 can be physically separatedfrom the high-energy beamline volume with a gate valve 177. A functionof the gate valve 177 is to separate the vacuum volume of the beamlinefrom the target 196 during target exchange/loading. In someimplementations, the beam instead of being bent by 90 degrees by abending magnet 156, can be directed straight to the right to enter thequadrupole magnets 152, which are located in the horizontal beamline.The beam could be bent by another bending magnet 158 to a preset angle,depending on a setting requirement (e.g., location of a patient or aroom configuration). In some implementations, bending magnet 158 can bearranged at a split in the beamline and can be configured to direct thebeam in one of two directions for two different treatment rooms locatedon the same floor of a medical facility.

FIG. 2A is a perspective view of the target 196 and FIG. 2B is across-sectional view of the target 196 illustrating cooling channels. Inthis embodiment target 196 is disk shaped with a generally circularouter profile. The target 196 generally includes one or more targetlayers 201 supported by a substrate 203. The side of the substrate 203includes channels 204 for a coolant. A scannable surface 210 is presenton target layer 201, which is the surface of target layer 201 that canbe scanned by the proton beam to produce neutrons. The target layers 201include a neutron source layer, such as a layer of lithium, beryllium,or other suitable material that interacts with the proton beam 104 toproduce a neutron flux. The thickness and composition of the one or moretarget layers 201 can vary depending on the properties of the protonbeam and the desired neutron flux. For example, a lithium based targetlayer can have a thickness in a range from about 10 microns (μm) toabout 400 μm. The target layer 201 can be adhered to the substrate 203via a thermal bond.

The substrate 203 can include one or more layers of copper, aluminum,stainless steel, titanium, and/or molybdenum. The target layer 201,including a reactive metal, can form an amalgam with the substrate 203.The characteristics of the target 196 (e.g., layer thickness,composition, and bond type) are associated with an onset of blisteringat particular levels of particle doses per target surface.

Channels 204 can be used to circulate coolant across the backside ofsubstrate 203 during operation of the system 100, in order to dissipateheat produced by absorption of kinetic energy from slowing in substrate203 of the protons that did not participate in the reaction.Alternatively, or additionally, coolant can be provided as a fluidchamber in contact with at least a portion of the substrate 203. Forexample, coolant channels can be formed as capped through-holes thatcross the substrate 203 and define closed fluid passages with a varietyof different geometries (e.g., circular or rectangular cross sections)and dimensions (e.g., cross sectional diameters ranging from about 0.5millimeters (mm) to about 3 mm).

The target 196 can be supported by a support structure (e.g., a shaft111 or a base 112). The support structure can be configured to maintainthe target 196 in a fixed position or to rotate the target 196 clockwise114 or counterclockwise (CCW) in a vertical plane including a verticalaxis 116 that is nominally perpendicular to the beam axis. The particlebeam 104 can be dynamically directed towards the target 196 according toa particular pattern (e.g., spiral, curved, stepped in rows and columns,combinations thereof, and others) that may change over time. The patterncan be repeated at a given frequency. In some implementations, both thetarget 196 and the beam 104 move relative to the beam axis duringoperation, such that segments of the rotatable target 196 can besequentially contacted by the beam 104 to form a scanning pattern, asdescribed in detail with reference to FIGS. 3A-3C, 4A-4G, and 7A-7F. Asa result of the interaction of the beam 104 with the target layer 201(e.g., neutron source layer), a beam 106 (e.g., neutron beam) isgenerated and directed (e.g., via a collimator or other beam-shapingstructure) towards a treatment area of the patient 108.

FIG. 2C is a cross-sectional view of another example embodiment, wheretarget 196 includes an intermediate layer 202 located between the targetlayer 201 and the target substrate 203. The intermediate layer 202 canreduce the likelihood of blister formation within the target 196 due tothe impingement of the beam. The intermediate layer 202 can be composedof thermally conductive materials that are resistant to blistering, suchas tantalum.

During operation of the beam system 102, the proton beam 104 is directedat scannable surface 210 of target 196. In order to avoid overheating,the proton beam 104 is moved at a rapid rate in two or more directions(e.g., X and Y) across surface 210, which is a process referred to asscanning. The path that the beam takes across surface 210 determines theamount of heating that occurs at different locations across surface 210and relative differences in particle loading on target 196. The beampath can be conformed to the capabilities of the system to cool thetarget 196 and the capability of the target 196 to withstand variancesin particle loading.

FIG. 3A is a schematic view depicting an example pattern 300 formed by apath 301 that a beam takes across surface 210. The outer boundary of thebeam cross-section is indicated by cross-sectional profile 320, which inthis example is circular. Pattern 300 of path 301 is curved withmultiple loops, or orbits, created as the beam proceeds from an outerregion of surface 210 to an inner region and then back again to theouter region. Beam path 301 includes a starting location A and astopping location O. The locations A, O can be the same single locationor different locations. In some embodiments, the starting and stoppinglocations A, O can be the same position or in close proximity to eachother (e.g., adjacent positions, or positions within one beam diameterof each other).

Path 301 starts at location A and proceeds in a CCW manner indicated byarrow B. Path 301 continues in an inwardly directed spiral fashion(e.g., with continually decreasing radius) as indicated by arrows C, D,E, F, G, and H. Arrow H indicates entry of beam path 301 into thesmallest radius orbit until reaching location I, which marks theposition where the beam path radius transitions from a continuallydecreasing radius to a continually increasing radius. In other words, atlocation I, beam path 301 begins to transition from the inner region ofsurface 210 back towards the outer region. Arrow J indicates the path ofbeam 301 from location I in counterclockwise manner in an outwardlydirected spiral fashion (e.g., with continually increasing radius) asindicated by arrows K, L, M, and N until reaching stopping location O.At this point path 301 has completed a transition from the outer regionto the inner region and back to the outer region of surface 210. A pathwith at least one orbit about a central point, that has a starting and astopping location at the same distance (or radius) from the centralpoint, and that traverses between a minimum distance (or radius) fromthe central point and a maximum distance (or radius) from the centralpoint, is referred to as a cycle. The starting and stopping locationscan be at any distance between (and including) the minimum distance andthe maximum distance. In this case, the single cycle forms a closed loopsuch that stopping location O is substantially at or adjacent tostarting location A.

Pattern 300 can cover a majority of the surface area of the scannablesurface 210 of the target. In this example beam profile 320 is largeenough such that area of surface 210 impinged upon by the beam willoverlap as the beam transitions through each orbit. Stated differently,the width of beam profile 320, measured perpendicular to the directionof travel of the beam, is greater than a distance between adjacentorbits. The pattern 300 is symmetrical along axis 330, such that a firsthalf 332 of pattern 300 is a mirror image of a second half 334 ofpattern 300. The outward to inward portion of path 301 from location Ato location I is a mirror image of the inward to outward portion of path301 from location I to location O.

While path 301 is described as transitioning in a CCW fashion, from theouter region to the inner region and back, the embodiments describedherein are not so limited. For example, in some implementations, thebeam can utilize a path that follows a clockwise (CW) rotation startingat the inner region, transitioning to the outer region and then back tothe inner region (one cycle). Path 301 can complete an entire cycle oronly a portion of a cycle, for example, involving a transition from theinner region to the outer region or the reverse.

FIGS. 3B and 3C are schematic views depicting examples of differentpaths taken with different beam cross-sectional profiles. In FIG. 3B, anelliptical (e.g., oval) beam profile 342 having a greater X dimensionthan Y dimension follows a path 341 sized such that the beamcross-sectional profiles of adjacent orbits touch but do not overlapwhen aligned along a central X axis. With constant spacing betweenorbits the beam will leave gaps, as is most evident when aligned alongthe Y axis. To cover the entire area with a minimal level of exposure,the overall path would need to be made elliptical with an aspect ratiosimilar to profile 342 with a smaller total Y dimension than Xdimension. FIG. 3C shows an example with circular cross-sectionalprofile 352 taking a path 351. While no gaps exist in FIG. 3C, theamount of orbits is greater (just over 4, as compared with 3.75 for FIG.3B).

FIGS. 4A-4B are schematic views depicting an example embodiment of ascanning (or raster) profile 400 formed by a cycle 405 scanned multipletimes at different radial orientations to form a group of radiallyshifted instances of the cycle. In this embodiment each instance ofcycle 405 has the same pattern and a stopping location that differs fromthat instance of cycle 405's starting location. FIG. 4A depicts a cycle405 formed by a beam path 406 where starting position A and stoppingposition O are in different locations that, in this example, are offsetby 180 degrees. Cycle 405 is rotatable or clockable for repetition atdifferent radial orientations to form a closed loop.

Scanning profile 400 is depicted in FIG. 4B. Here, scanning profile 400includes two instances of cycle 405 with a difference of 180 degrees inradial orientation between them. The first instance of cycle 405 isshown by path 401, which is depicted with starting location A1, midpointI1, and stopping location O1 in the same positions as in FIG. 4A. Thesecond instance of cycle 405 is shown by path 402, which has startinglocation A2, midpoint I2, and stopping location O2. Path 402 has thesame shape as path 401 but has been rotated (or clocked) by 180 degrees.For example, clocking forward can be implemented by evenly advancing thetransformed theta coordinate over the A1 to O1 cycle, such that O1 ends180 degrees off A1. Every location on path 401 is radially offset fromthat same or corresponding position on the next path 402 in the sequenceby the same radial amount. Each of locations A2, I2, and O2 are shown inpositions 180 degrees from A1, I1, and O1, respectively. In this and theother embodiments described herein, the clocking of cycles can beperformed in a CW or CCW direction.

The stopping location of a first cycle (e.g., O1) is at or adjacent tothe starting location of the immediately subsequent shifted cycle (e.g.,A2), such that the beam can move in uninterrupted fashion from instanceof cycle 405 to the next. The starting location A1 of the first cycle(e.g., path 401) and the stopping location O2 of the last cycle of thegroup (e.g., path 402) is substantially the same or adjacent to eachother. Thus, the profile formed by the group of two or more radiallyshifted cycles has the same (or adjacent) starting and stoppinglocations, and forms a closed loop. A group of two or more cycles eachhaving the same pattern, where each cycle has a starting location and astopping location at the same distance (or radius) from a central point,and each cycle is rotatable in orientation such that adjacent cycles canbe concatenated together to form a closed loop for the group, isreferred to herein as a super cycle. Scanning the target 196 can involvemoving the beam through a first cycle at a first radial orientation(e.g., path 401), then moving the beam through the same cycle at leastone more time (e.g., path 402) but with the subsequent cycle at a radialorientation different from that of the first cycle. This process repeatsuntil the super cycle is completed, at which time the process ofscanning repeats itself. The scanning process can be continuouslyrepeated until the overall procedure, e.g., the BNCT treatment, iscomplete.

The terms radial orientation, radial shift, and radial offset are usedherein to describe a cycle that, as a whole, can be rotated (or clocked)about a central point without changing the cycle's fundamental shape.For example, in FIG. 4A, cycle 405 has a first radial orientationindicated by path 401. Cycle 405 is then radially (circumferentially)shifted by 180 degrees to the second radial orientation indicated bypath 402. The radial offset between the two instances 401, 402 of cycle405 is 180 degrees. The characterization can be similarly expressed bysubstituting the term azimuthal for radial (e.g., azimuthal orientation,azimuthal shift, and azimuthal offset). For example, a value of thetacan define a position of an azimuth about a central point on thescannable surface (similar the hour hand of a clock, where an azimuth ata three o'clock position corresponds to a theta of 90 degrees, at sixo'clock is a theta of 180 degrees, at nine o'clock is a theta of 270degrees, etc.), and positions of cycles can be expressed with referenceto theta and the azimuth.

FIGS. 4C and 4D are schematic views depicting a cycle 415 that isrepeated four times with a difference of 90 degrees in radialorientation between adjacent instances to form another example ofscanning profile 400. In FIG. 4C, cycle 415 is formed by a beam path 411which starts at location A1 and proceeds in CCW fashion to midpoint I1in the inner region of surface 210, and then back to the outer region atstopping location O1. Stopping location O1 is radially offset CCW fromstarting location A1 by 90 degrees, which is the same amount of radialoffset that is present between the cycles 415 of this profile 400. FIG.4D depicts a second instance of cycle 415 indicated by path 412 havingstarting location A2, midpoint I2, and stopping location O2. FIG. 4E isthe same as FIG. 4D but with a third instance of cycle 415 added asindicated by path 413 having starting location A3, midpoint I3, andstopping location O3. FIG. 4F is the same as FIG. 4E but with a fourthinstance of cycle 415 added as indicated by path 414 having startinglocation A4, midpoint I4, and stopping location O4, to form thecompleted super cycle of scanning profile 400. When this embodiment ofscanning profile 400 is used, the beam is transitioned through path 411,then path 412, then path 413, and then path 414 to complete the supercycle, and this super cycle can then be repeated continuously throughoutthe entire procedure.

In the example illustrated by FIG. 4G, the scanning profile 400 is asuper cycle including three instances 421, 422, 423 of the same cyclebut with a difference of 120 degrees in radial orientation betweenadjacent ones. The cycle of FIG. 4G is modified from that of FIG. 4A topermit three iterations with one closed loop. The second instance 422 isradially shifted CCW by 120 degrees from first instance 421, and thirdinstance 423 is radially shifted CCW by 120 degrees from instance 422(radially shifted CCW by 240 degrees from instance 421). Each oflocations A2, I2, and O2 are shown in positions 120 degrees CCW from A1,I1, and O1, respectively, and each of locations A3, I3, and O3 are shownin positions 120 degrees CCW from A2, I2, and O5, respectively. The beamis transitioned through instance 421, then instance 422, and theninstance 423 to complete the super cycle. The super cycle can berepeated continuously multiple times throughout the entire procedure.

Additional example embodiments of scanning profile 400 can also beimplemented. The amount of radial offset between the repeated patterns301 can be determined by dividing 360 degrees by the number of patterninstances. For example, a profile 400 having five instances of a cyclecan have a radial offset of 72 degrees between adjacent cycles, aprofile 400 having six instances of a cycle can have a radial offset of60 degrees between adjacent cycles, a profile 400 having seven instancesof a cycle can have a radial offset of approximately 51.4 degreesbetween adjacent cycles, a profile 400 having eight instances of a cyclecan have a radial offset of 45 degrees between adjacent cycles, aprofile 400 having nine instances of a cycle can have a radial offset of40 degrees between adjacent cycles, a profile 400 having 10 instances ofa cycle can have a radial offset of 36 degrees between adjacent cycles,a profile 400 having eleven instances of a cycle can have a radialoffset of approximately 32.7 degrees between adjacent cycles, a profile400 having twelve instances of a cycle can have a radial offset of 30degrees between adjacent cycles, and so forth.

In some implementations the stopping location of a first instance of thecycle may not be the same as, or even close to, the starting location ofthe next instance of the cycle. For example, the beam can bridge the gapin a relatively rapid fashion that has negligible effect on the overallthermal performance and particle loading. If the beam is pulsed, theradial shift can occur in between pulses while the beam is off.

While the embodiments described herein are shown with the same cyclerepeated multiple times within a super cycle, it is noted that the cyclepattern need not be identical and differ only in radial orientation. Inpractice small variations will inherently be present given margins oferror within the system and variances of operating conditions during theprocedure. Indeed the scope of the present subject matter coversembodiments where the repeated cycle patterns are not identical, but arerather substantially the same with differences engendered by margins oferror, operating condition variances, and even programmed or otherwiseintended non-identicalities in the patterns.

In general, the thermal impact of a beam on the target can beinvestigated computationally using a computational model. Computationalmodelling can allow for selection of beam raster profiles that improveuniformity of particle loading on a target and/or can allow selection ofraster profile that reduces (e.g., minimizes) peak transient temperatureof the target. The raster profile can be characterized by a beam pathand a beam profile (e.g., circular or elliptical beam with a particulardimension), as described with reference to FIGS. 8 and 9 . In someimplementations, the raster profile can define a beam scanning velocity.

The computational model can allow investigation of the effect on atarget of varying one or more of several beam parameters, such as thebeam's size and shape. Furthermore, the beam's thermal impact can beevaluated by calculating one or more figures of merit (e.g., peaktemperature, temperature change, average temperature) and applying anumerical analysis to the figure of merit can allow the computationalmodel to be used to optimize the beam's raster profile.

Generally, the computational model can involve generating a meshed spaceencompassing the target. The computational model is illustrated in FIGS.5A and 5B, which illustrate a mesh composed of a three-dimensional gridin which the heating (temperature map) of target 196 can be modeled. Thetemperature values are modeled by solving a one-dimensional heattransport equation at each “pixel” (e.g., each x-y square of the gridshown in 5A). The one-dimensional heat transport equation(u_(t)=c²u_(xx), defining the temperature in a pixel using the constantc as the thermal diffusivity) is solved for thermal transport throughthe depth of the pixel, in Z direction, as shown in 5B. Cross talkbetween pixels or lateral heat conduction between pixels is assumed tobe negligible, such that heat only moves horizontally in Z direction,allowing the 1D approach to be used. The beam is considered to generatea propagation of heat for a particular depth into each pixel (e.g.,approximately 25% of the beam energy is deposited evenly through thelithium layer and the remaining energy is deposited into the firstelement of the copper), corresponding to the incident beam.Compositional changes are accounted for through the depth of the pixel.Any suitable computational approach to solving the one-dimensional heattransport differential equation can be used. For example, numericalapproaches can include finite-element and finite-difference approaches.For either of the finite-element and finite-difference techniques, thetarget 196 can be represented in a plan view 220 as a portion of a grid226 (as illustrated in FIG. 5A). The size of the grid can vary and canbe selected based on the size of the target, the beam size, and thedesired computational efficiency and result accuracy. Generally, asmaller size can give more accurate answers but at computational cost.In the current example shown in FIG. 5A, the grid 226 includes 36×36pixels (cells), but generally, the number of pixels can be within therange 10³-10⁵ or more.

Generally, the grid can have the same unit cell size in each dimensionor the size in each dimension can differ. Resolution can be selected toprovide the ability to model beams of different size and structure inline to the physical capabilities of the system under study.

FIG. 5B is an example of a model of a target side view 230 of the target196 illustrated in FIG. 2A. The model of the target side view 220includes multiple layers that can correspond to the layers 201, 202, 203described with reference to FIGS. 1B and 2C. In some implementations,the layers can have a thickness defined by the pixels of the numericalgrid 226. In some implementations, a boundary of the target layer 201 ismodeled as corresponding to vacuum and a boundary of the targetsubstrate 203 is modeled as corresponding to a coolant fluid (e.g.water), defining the boundary conditions of the one-dimensional heattransport equation.

FIGS. 6A-6D show examples of simulated thermal maps using the modeldescribed with reference to FIGS. 5A and 5B. FIGS. 6A and 6B showexamples of simulated thermal maps 610, 620 determined using thecomputational model as described above for 10 mm and 20 mm beam sizes,respectively. FIGS. 6C and 6D show examples of simulated thermal maps630, 640 determined using an ANSYS® engineering simulation software for10 mm and 20 mm beam sizes, respectively. The model used to generate thesimulated thermal maps 610, 620 is based on a transient code that tracksthe surface particle loading based on any given beam profile incombination with any raster profile. The model was benchmarked against atransient model calculated with a three-dimensional heat transfer codeANSYS® as validation.

The overall profile of the simulated thermal maps 610, 620, 630, 640calculated based on assumption of a scanning frequency of 120 Hzgenerally matches for both 10 mm and 20 mm beam sizes. For example,FIGS. 6A and 6C both show a surface temperature distribution with adistinctive heat maximum corresponding to the center of the 10 mm protonbeam. The highest average lithium surface temperature was 284° C. asdetermined by the model and 299° C. as determined by the ANSYS® model.The temperature drop from the center of the 10 mm proton beam to themargins of the 10 mm proton beam registered 162.7° C. as determined bythe model and 177.7° C. as determined by the ANSYS® model. FIGS. 6B and6D both show a dispersed surface temperature distribution correspondingto the 20 mm proton beam. The highest average lithium surfacetemperature was 177° C. as determined by the model and 184° C. asdetermined by the ANSYS® model. The temperature drop from the center ofthe 20 mm proton beam to the margins of the 20 mm proton beam registered55.7° C. as determined by the model and 63.3° C. as determined by theANSYS® model The fact that some of the calculated temperature values areabove the acceptance limit for Lithium shall not undermine the validityof the model.

Table 1 shows heating map simulation results that enable a comparisonbetween the predicted temperature variation (ΔT) and peak temperature(T_(max)) as determined using the model described with reference toFIGS. 5A and 5B and using an ANSYS® engineering simulation software. Thedata was generally analyzed to determine the correlation between themodeled values with respect to the values determined using thecomputationally expensive ANSYS® engineering simulation software todetermine the reliability of the developed model. The reliability of themodel is reflected by the differences in the thermal results. Atemperature rise difference of about 10% was found between the two setsof results, indicating agreement between the model and the transientANSYS® model.

TABLE 1 Model ANSYS % Diff Model ANSYS (10 mm) (10 mm) (10 mm) (20 mm)(20 mm) % Diff ΔT 162.7° C. 177.7° C. 8.44% 55.7° C.  63.3° C. 12.01%T_(max)   284° C.   299° C. 5.02%  177° C. 184.6° C.  4.11%

As is evident from the raster patterns shown in FIGS. 3A-5G, there arenumerous points in each pattern where the beam path crosses itself. Eachcrossing point is a location where the target surface is exposed to asignificantly higher particle flux (e.g., double) than locations wherethe target surface is exposed just a single time for each super cycle.Where the time between consecutive passes over a crossing point isrelatively long, and heat from the first pass can be sufficientlydissipated before the second exposure, the increased dose associatedwith the second exposure may not result in excessive heating at thecrossing point. However, where a crossing point is exposed twice in arelatively short period, these crossing points can be locations ofunacceptably high thermal loads. Accordingly, in some implementations,the computational models described above can be used to reduce thermalload on a target by determining paths that reduce the number of crossingpoints that experience multiple passes of the beam in quick succession.

For example, a computational model can be used to vary parameters of araster profile to avoid crossing the beam path recently traversed withina threshold time period below which excessive heating of that targetlocation may occur. FIGS. 7A-7F are schematic views depicting examplesof raster patterns that are instructive in demonstrating such recentpath avoidance (RPA) strategies. In some implementations, the RPApattern can be determined based on an iterative process. The iterativeprocess can start with a trochoid shape, defined as an (x(t), y(t))position for a given time (t). For radii, r₁, r₂ and frequencies ω₁, ω₂,the basic trochoid follows the following equations over time t:x(t)=r ₁ cos(ω₁ ·t)+r ₂ cos(ω₂ ·t)y(t)=r ₁ sin(ω₁ ·t)+r ₂ sin(ω₂ ·t).

For an L-lobed trochoid with outer radius, r_(max), and inner radius,r_(min), the values for the radii and frequencies are:r ₁=−(r _(max) +r _(min))/2r2=(r _(max) −r _(min))/2ω₁ =L+1ω₂=1

A radius with a maximum radius value r_(max) substantially equal to thebeam width and a minimum radius value r_(min) substantially equal tohalf the beam width can provide good results for a uniform-intensitybeam. Optimal values for r_(max) and r_(min) can be found throughoptimization algorithms and a heat simulation code.

Setting t to be time dictates the speed at which the raster moves, whichcan be varied based on capabilities of the steering magnets and a targetburning risk. For example, a high raster speed may exceed the capabilityof the steering magnets or a low raster speed may lead to burning of thetarget (if exposed too long to a particular radiation dose). For allmodified trochoid raster profiles, the next beam position is calculatedsuch that the velocity remains approximately constant. Varying thevelocity based on the beam position may offer another route forimprovement. The optimal velocity profile can be found by training amachine-learning algorithm on the results generated by the heatsimulation code, as described with reference to FIGS. 8A, 8B, 9A, and9B.

A constant-velocity trochoid pattern can give good results in targetusage but could lead to overheating. For example, the trochoid patternvisits the center of the target with a fairly high frequency because asthe trochoid path continuously follows each lobe. In order to solve theheating problem, the raster pattern can be modified such that instead offollowing the path along each lobe continuously, the ω=(L−1)^(th) lobeorder is used. Visiting the lobes in this order gives the centeradditional time to cool down between lobes. This is where the nameRecent Path Avoidance (RPA) raster comes from, as recently visited pathsare avoided, prolonging the time it takes for the beam to cross itsrecent path. For some values of L, it may be optimal to take lobes morefrequently than every ω=(L−1)^(th) lobe. Any lobe frequency, ω that iscoprime with the total number of lobes, L, could work depending on thephysical parameters of the system (beam profile, target shape, targetmaterial, etc.). The choice of lobe frequency ω can be optimized throughcomputational techniques, such as using a machine learning algorithm.

In some implementations, the raster path includes a modification of r₁and r₂ to create a filter that only allows the raster path to followevery (L−1)^(th) lobe and otherwise to follow the r_(max) value to allowthe center of the target time to cool down.

For example, an initial RPA raster (RPA One) can include the followingradii and frequencies:

$r_{1} = {{- ( {r_{\max} + r_{\min}} )} \cdot {\cos( {\frac{L}{2 \cdot ( {L - 1} )} \cdot t} )}^{E}}$r₂ = r_(max) ω₁ = L + 1 ω₂ = 1

The exponent E can be greater than 10 and smaller than 1000 (10<E<1000).The exact value of the exponent E can depend on multiple factors. Forexample, E can be set to be large enough to give a well-defined windowfor the filter to avoid having the raster oscillate around theperimeter, which may cause the beam to miss the target. E has to be setsmaller than a threshold value that defines a very small window thatwould cause the lobes to become too narrow, overheating the target. Insome implementations, E can be set such that E=100·(L−3) with L beinggreater than or equal to 4 and smaller than or equal to 8 (4≤L≤8).

RPA-One works well for minimizing heating, but can leave a region of thetarget underutilized. RPA-One can be used to develop RPA-Two, which addsanother term to r₁, to define another set of L lobes that can fill inthe underused region. RPA Two uses the following radii and frequencies:

$r_{1} = {{{- ( {r_{\max} + r_{\min}} )}{\cos( \frac{L \cdot t}{{2L} - 1} )}^{E}} - {r \cdot {\cos( \frac{L \cdot t}{2 \cdot ( {{2L} - 1} )} )}^{E}}}$r₂ = r_(max) ω₁ = 2L + 1 ω₂ = 1

The coefficient r can be greater than r_(min), and smaller than thedifference between the radii limits r_(max) and r_(min)(r_(min)<r<r_(max)−r_(min)). The exponent E can be greater than 100 andsmaller than 10000. The exact values of the coefficient r and exponent Ecan be optimized using the heat simulation and an optimizationalgorithm. In some implementations, one or more additional rasters(RPA-N) can be determined by adding terms to r₁, each new term can beoptimized to minimize target heating and target usage variation.

FIG. 7A illustrates an example of a trochoid raster pattern 700 that canbe generated by directing the beam towards a (static or rotating)target. The trochoid raster pattern 700 can be used as an initial rasterpattern for an iterative process, as described with reference to FIG. 10. The trochoid raster pattern 700 can include multiple lobes 702, 704,706, 708 (e.g., 4 four lobes as illustrated in FIG. 7A). In someimplementations, the values for the inner radius 701 and the outerradius 703 can be found through optimization algorithms and by using theheat simulation code described above with reference to FIGS. 5A and 5B.The trochoid raster pattern 700 includes multiple beam crossing points705 a, 705 b, 705 c, 705 d, 705 e, 705 f, 705 g, 705 h, 705 i, 705 j,705 k, 705 l, 705 m, 705 n where the beam path crosses itself. Forexample, considering the startup point 705 of the trochoid rasterpattern 700, the first beam crossing point is 705 a, the second beamcrossing point is 705 b, the third beam crossing point is 705 c, thefourth crossing point is 705 d, and the fifth crossing point is 705 e.

FIG. 7B illustrates an example of a modified raster pattern 710, whereinthe order of the lobes 702, 708, 706, 704 is modified to extend thecooling period of the points where the beam path crosses itself,generating a recent path avoidance (RPA) pattern. The time durationbetween subsequent beam crossing points is directly proportional to thearc length traversed by the beam between respective consecutivecrossings. For example, considering the startup point 705 of themodified raster pattern 710, the first crossing point is 705 g, which isassociated with a longer arc length than the arc length corresponding tothe first crossing point 705 a of the trochoid raster pattern 700.

In some implementations, the RPA pattern can be further modified to fillunderused regions of the target, as described with reference to FIGS.7C-7F.

FIGS. 7C-7F are schematic views depicting examples of recent pathavoidance (RPA) patterns 720 that are repeated multiple (e.g., four)times to form a full super cycle of the scanning profile. FIG. 7Cillustrates the first cycle 722 of the RPA pattern. The first cycle 722of the RPA pattern 720, starting at 722A and stopping at 7220, includesmultiple beam crossing points 725 a, 725 b, 725 c, 725 d where the beampath crosses itself. For example, considering the startup point 722A ofthe first cycle 722 of the RPA pattern 720, the first beam crossingpoint is 725 a, the second beam crossing point is 725 b, the third beamcrossing point is 725 c, and the fourth crossing point is 725 d.

FIG. 7D illustrates the second cycle 724 of the RPA pattern 720 that canbe performed after the completion of the first cycle of the RPA pattern.The second cycle 724 of the RPA pattern 720, starting at 724A andstopping at 7240, includes multiple beam crossing points 735 a, 735 b,735 c, 735 d where the beam path crosses itself. For example,considering the startup point 724A of the second cycle 724 of the RPApattern 720, the first beam crossing point is 735 a, the second beamcrossing point is 735 b, the third beam crossing point is 735 c, and thefourth crossing point is 735 d.

FIG. 7E illustrates the first two cycles 726 of the RPA pattern 720. Thefirst two cycles 726 of the RPA pattern 720 include the beam crossingpoints 725 a, 725 b, 725 c, 725 d of the first cycle 722, the beamcrossing points 735 a, 735 b, 735 c, 735 d of the second cycle 724 andbeam crossing points 745 a, 745 b, 745 c, 745 d, 745 e, 745 f, 745 g,745 h, 745 i, 745 j, 745 k, 7451, 745 m where the path of the secondcycle 724 crosses the path of the first cycle 722.

FIG. 7F illustrates the full super cycle 728 of the RPA pattern 720. Thefull super cycle 728 of the RPA pattern 720 includes the beam crossingpoints of each cycle (e.g., beam crossing points 725 a, 725 b, 725 c,725 d of the first cycle 722, the beam crossing points 735 a, 735 b, 735c, 735 d of the second cycle 724) and the beam crossing points where thepath of one cycle intersects the path of another cycle.

Each cycle of the RPA pattern 720 includes a stopping position 7220,7240 distanced from a starting position of the corresponding cycle 722A,724A. The stopping position of a cycle (e.g., stopping position 7220 ofthe first cycle) corresponds to the starting position of the subsequentcycle (e.g., starting position 724A of the second cycle). As illustratedin FIG. 7F, the RPA pattern 720 is formed by beam path 728, which startsat location 722A and proceeds in CCW fashion along four cycles(including the first two cycles 726 illustrated in FIG. 7E), and thenback to the starting position 722A. The example RPA pattern 720illustrated in FIG. 7F forms a raster profile with four cycles that forma closed pattern based on a single full super cycle to close the loop.

FIGS. 8A and 8B show examples of a simulated boundary temperature map802 and a simulated target usage map 804 corresponding to targetscanning using the RPA pattern described with reference to FIG. 7B, fora continuous path following the RPA pattern with constant velocity.Boundary temperature map 802 defines the boundary between lithium andcopper layers of the target, considering neutronic models that identifythe boundary as highest energy deposition layer with the hottestmeasured or modeled temperature. The target usage map 804 indicates howmuch lithium is consumed by each portion (pixel) of the target inresponse to the irradiation with the proton beam that is directedtowards the target using the RPA pattern.

The simulated boundary temperature map 802, as illustrated by FIG. 8A,includes a circularly dispersed heat maxima corresponding to the mostused cells, as illustrated by the simulated target usage map 804 of FIG.8B. The highest peak temperature within the simulated boundarytemperature map 802 was less than 150° C. The temperature variationacross the target surface within the simulated boundary temperature map802 was about 40° C. The simulated boundary temperature map 802 and thesimulated target usage map 804 indicate that scanning the target usingthe using the RPA pattern is efficient in preventing target damagethrough blisters or bubbles.

Additional modeling using the transient code provides several figures ofmerit for evaluating target performance. The figures of merit include:peak temperature, temperature change, average temperature, usageefficiency, nominal frequency, and beam shape. The peak temperatureincludes the maximum temperature found in the target at any time. Thetemperature change includes maximum temperature found in the target atany time minus the initial target temperature. The average temperatureis the average of the temperatures of all cells in the target. The usageefficiency includes the total target beam flux divided by the usage ofthe maximally used cell normalized to the total number of cells withinthe target. The results of the modeling using the transient code forevaluating target performance, in response to one super cycle or supercycles that are repeated multiple (e.g., 4) times, are included in Table2.

TABLE 2 Figure of Merit 1 Super cycle 4 Super cycles Peak Temperature140 140 Temperature Change 18.8 18.5 Average Temperature 133 133 UsageEfficiency 66.4% 73.5% Nominal OD Frequency 240 Hz 240 Hz Beam OD/shape20 mm round 20 mm round

FIGS. 9A-9J show examples of simulation results for multiple beamprofiles to compare target heating and target usage. Each simulationuses raster pattern 300 to highlight variation caused by the differentbeam profiles themselves. FIGS. 9A and 9B show the simulated thermal map902 and the simulated usage map 904, respectively for a 20 mm circular(not hollow) beam having a frequency of 120 Hz. FIGS. 9C and 9D show thesimulated thermal map 906 and the simulated usage map 908, respectivelyfor a 10 mm circular (not hollow) beam having a frequency of 120 Hz.FIGS. 9E and 9F show the simulated thermal map 910 and the simulatedusage map 912, respectively for a 15 mm by 25 mm elliptical (not hollow)beam having a frequency of 120 Hz. FIGS. 9G and 9H show the simulatedthermal map 914 and the simulated usage map 916, respectively for a 20mm annulus (hollow) beam with 10 mm hole, having a frequency of 120 Hz.FIGS. 9I and 9G show the simulated thermal map 918 and the simulatedusage map 920, respectively for a 10 mm circular (not hollow) beamhaving a frequency of 240 Hz.

Table 3 shows the simulation results for multiple beam profiles andraster patterns that enable a comparison between the percentage of usageand peak temperature (T_(max)) as determined using the model describedwith reference to FIGS. 5A and 5B. The data was generally analyzed todetermine optimal beam profiles and raster patterns. For example, theresults of the simulations as illustrated in FIGS. 9A and 9C indicatedthat a 20 mm beam exhibits an even temperature distribution overall. Theresults of the simulations as illustrated in FIGS. 9B and 9D indicatedthat a 10 mm beam exhibits more uniform usage, particularly near theedges. The simulated thermal map 910 and the usage map 912 correspondingto the elliptical beam, as illustrated in FIGS. 9E and 9F, respectivelyshow an increased coverage along the orientation of the major axis ofthe elliptical beam. Comparing the results of the simulations asillustrated in FIGS. 9E and 9F to the results of the simulations asillustrated in FIGS. 9A and 9B indicates that an elliptically shapedbeam with approximately the same area as a circular beam produces lesseven temperature and usage distributions than the circular beam. Thesimulated thermal map 914 and the usage map 916 corresponding to theannulus beam, as illustrated in FIGS. 9G and 9H, respectively show adecreased peripheral coverage with uneven radial distribution. Comparingthe results of the simulations as illustrated in FIGS. 9G and 9H to theresults of the simulations as illustrated in FIGS. 9A and 9B indicatesthat using any kind of beam with a hole decreases efficiency andproduces a more uneven temperature distribution throughout the target.Comparing the results of the simulations as illustrated in FIGS. 9I and9J to the results of the simulations as illustrated in FIGS. 9A and 9Bindicates that using a 240 Hz beam produces a more even temperaturedistribution throughout the target and similar target usage.

TABLE 3 Profile CS CS CS CS CS RPA Parameters 240 Hz 240 Hz 240 Hz 240Hz 120 Hz 240 Hz Beam 20 mm 10 mm 15 × 25 mm 20 mm with 20 mm 20 mmParameters elliptical 10 mm hole (diameter) % Usage 58.8% 56% 58.3%57.8% 59.2% 68.4% T_(max) 148° C. 178° C. 152° C. 152° C. 162° C. 139°C.

FIG. 10 is a flowchart depicting an example process 1000 that can beexecuted in accordance with implementations of the present disclosure. Avariety of possible raster profiles for scanning a proton beam acrossthe target is established using a computer processing system (1002).Each raster profile defines a different scanning pattern of a target.Each scanning pattern includes multiple super cycles that form a closedpath on the target surface based on one or more cycles to close theloop. The scanning pattern can include a RPA pattern (e.g., trochoidshape including multiple lobes) as described with reference to FIGS.7A-7D or other scanning patterns described above. The scanning patterncan be characterized by one or more path parameters. In someimplementations, the parameters include one or more of the followingparameters: an angular frequency associated with each lobe of the pathof the proton beam, a linear velocity of the proton beam across asurface of the target, a number of radial scan layers in a super cycleof the path of the proton beam, a traversal order of the lobes, and anumber of super cycles of the path of the proton beam. The angularfrequency and the angular velocity of the proton beam can vary fordifferent lobes of the RPA pattern. The traversal order of the lobes canbe a forward order, a reverse order or a coprime order. The pathparameters characterize the path of the proton beam across the target.The path parameters of the selected raster profile define a path for theproton beam having a minimum delay (exceeding a threshold period)between successive exposures of a single location of the target to theproton beam to minimize target damaging. In some implementations, thepossible raster profiles include a masked profile that can be formedbased on real time measurements based on imaging data (e.g., thermalmaps of the target). The masked profile can define a scan profileconfigured to avoid portions of the target including weak areas (e.g.,areas heated near to the melting point) or damaged regions of thescannable area of the target.

In addition to a scanning pattern, each of the raster profiles includessettings for one or more beam parameters. Each of the beam parameterscharacterizes a property of the proton beam. The beam parameters caninclude one or more of the following parameters: a beam dimension (e.g.,a diameter of a circular beam), a beam shape, and a beam structure. Insome implementations, the beam dimension is in a range from 10 mm to 30mm. Raster profiles can be modified with a normalization coefficient inthe X and Y direction depending to the beam shape. The beam shape can becircular or elliptical. If the beam shape is elliptical, the scan can bemodified to change effectively by lowering the scan radius in thedirection that the beam is the largest so that the beam does not scanoutside the outer boundary. The structure of the beam refers to the beamintensity distribution across its cross section. In someimplementations, the distribution can be substantially constant orGaussian. In certain implementations, the distribution can have morethan one peak, such as for an annular beam structure.

One or more target parameters characterizing the target are alsoestablished using the computer processing system (1004). For example,the target parameters can include of: target surface area, targetthickness, and/or target composition.

A value of a figure of merit is calculated for each of the possible beamraster profiles (1006). Generally, the figure of merit is based on athermal loading of the target by the proton beam for the correspondingpossible raster profile. In some implementations, calculating the valuesfor the figure of merit includes, for each of the possible rasterprofiles, calculating a thermal load at each of a plurality of discreteportions of the target based on a linear relationship between thethermal load and a proton flux at each discrete portion for thecorresponding raster profile. In some implementations, each discreteportion corresponds to an area of a surface of the target in the path ofthe proton beam that is smaller than a dimension of the proton beam. Insome implementations, the thermal load at each discrete portion iscalculated based on heat transfer through a depth of the target awayfrom a surface of the target on which the proton beam is incident. Insome implementations, the figure of merit is selected from the groupconsisting of: a peak temperature of the target, a temperature change ofthe target, an average temperature of the target, and a usage efficiencyof the target.

A raster profile is selected from among the possible raster profilesbased on the value of the figure of merit and based on the measuredproperty of the target (1008). In some implementations, the selection ofthe raster profile includes a presentation of an operator of the protonbeam with a list of the possible raster profiles and receiving, via auser interface of the computer system, a user input including aselection from the list by the operator. In some cases, raster profileselection can occur automatically, e.g., based on measurements of eitherthe beam properties, target properties, or both. For instance, where athreshold level of heating is detected on the target, the system canswitch to a different raster profile that puts less stress on thelocation where the threshold load is detected. In some implementations,the system uses an active feedback or feedforward process andperiodically adjusts the raster profile to prolong the useful life ofthe target.

In some implementations, multiple raster profiles can be selected ascandidate profiles, F_(k)(t), and cutover functions, s_(k)(t), can beapplied to switch between profiles. The output profile, F (t), can bedefined by:F(t)=Σ_(k=1) ^(n) s _(k)(t)F _(k)(t),where Σ_(k=1) ^(n)=s_(k)(t)=1 for every value tin the domain of theoutput profile.

For example, a simple linear crossover between two profiles, F1(t) andF2(t), starting at t1 and ending at t2 could be described by definings1(t) and s2(t) as follows:

${s_{1}(t)} = \{ \begin{matrix}1 & {t < t_{1}} \\{1 - \frac{t - t_{1}}{t_{2} - t_{1}}} & {t_{1} \leq t \leq t_{2}} \\0 & {t > t_{2}}\end{matrix} $ ${s_{2}(t)} = \{ \begin{matrix}0 & {t < t_{1}} \\{0 + \frac{t - t_{1}}{t_{2} - t_{1}}} & {t_{1} \leq t \leq t_{2}} \\1 & {t > t_{2}}\end{matrix} $

After selection of a particular raster profile, the proton beam isscanned across the target according to the selected raster profile(1010).

One or more properties of the beam are measured (1012) as part ofprocess 1000. In some implementations, the properties of the beam aremeasured upstream from the target. The beam properties that can bemeasured include, for example, a beam size, a beam structure, and a beamprofile, as described with reference to FIGS. 9A-9J. The beam profilecan be measured using infrared cameras configured to determine the beamshape at the target location.

One or more properties of the target are measured (1014) as part ofprocess 1000. In some implementations, the one or more properties of thetarget include a temperature of the target at one or more locationsacross the target. For example, one or more thermal sensors (e.g.,infrared cameras) can detect the temperature of the target at acorresponding location. In some implementations, a temperature map ofthe target can be acquired by a thermal camera. The measured temperaturecan be used as an input to dynamically adjust or change the rasterprofile during the scanning process to avoid local overheating of thetarget. In some cases, the system can pause beam operation entirely toavoid overheating the target and resume operation once the target coolsto an acceptable level.

Thus, implementations of the present disclosure can include a number ofadvantages. In some examples, the described techniques provide accurateestimations of target heating and usage with minimized computationresource requirements. Designs described herein illustrate advantages ofparticular raster profiles and beam profiles that can extend thelifetime of a target, by maintaining peak temperature under the damaging(e.g., blistering) temperature of the target. The describedimplementations can also enable an improved performance of BNCT, byproviding an even distribution of particle loading on the target, whichpositively affects the profile of the particle beam that irradiates thepatient.

In one aspect . . . [the attorneys will include a claims bank here oncethe claims are finalized]

FIG. 11 is a block diagram showing an example system that can beimplemented in accordance with the present disclosure. For example, theillustrated example system 1100 includes a beam system 102 one or morecomputing devices 1102, and one or more servers 1110. In someimplementations, beam system 102 may be part of an example neutron beamsystem (e.g., system 102 described with reference to FIGS. 1A and 1B).The beam system 102 may employ one or more control systems 1101 withwhich one or more computing devices 1102 may communicate in order tointeract with the systems and components of the beam system 102 (e.g.,neutron beam system 102). The control system 1101 can be programmed tocontrol the steering devices (e.g., magnets, X-Y shifter) in HEBL 50that determine the X-Y position of the proton beam incident upon thescannable surface 210 of target 196. The beam system 102, the one ormore computing devices 1102, and one or more servers 1110 are configuredto communicate directly with one another or via a local network, such asnetwork 1104.

Control system 1101 can be programmed with parameters of amplitude andoffset controls that allow a fixed displacement of the beam to controllocation of the total scanned pattern. In some embodiments, theparameters are programmed in or for a digital signal processor (DSP)that controls the magnet power supply. The amplitude and offsetparameters can be input to the DSP in real time during operation, i.e.,on the fly, to correct for changes in the beam behavior or energy. Thereal time parameters can form a generalized method of active feedbackfor ion particle beam control.

Computing devices 1102 may be embodied by various user devices, systems,computing apparatuses, controllers, and the like. For example, a firstcomputing device 1102 may be a desktop computer associated with aparticular user, while another computing device 1102 may be a laptopcomputer associated with a particular user, and in yet another computingdevice 1102 may be a mobile device (e.g., a tablet or smart device).Each of the computing devices 1102 may be configured to communicate withthe beam system 102, for example through a user interface accessible viathe computing device. For example, a user may execute a desktopapplication on the computing device 1102, which is configured tocommunicate with the beam system 102.

By using a computing device 1102 to communicate with beam system 102, auser may provide operating parameters for beamline components 3005(e.g., operating voltages, and the like) according to embodimentsdescribed herein.

The control system 1101 may be configured to receive measurements,signals, or other data from components 1105 and monitoring devices 1103of the beam system 102. For example, the control system 1101 may receivesignals from one or more monitoring devices 1103 indicative of operatingconditions and/or a position of a beam passing through the beam system102. The control system 1101, depending on the operating conditionsand/or position of the beam passing through the beam system 102, mayprovide adjustments to inputs of one or more beam line components 1105according to the methods described herein. The control system 1101 mayalso provide information collected from any of the components of thebeam system 102, including the monitoring devices 1103, to the computingdevice 1102 either directly or via communications network 1104. Thecontrol system 1101 can be programmed to implement embodiments of thescanning profile as described with reference to FIGS. 4, 5, and 7-10 .

The communications network 1104 may include any wired or wirelesscommunication network including, for example, a wired or wireless localarea network (LAN), personal area network (PAN), metropolitan areanetwork (MAN), wide area network (WAN), or the like, as well as anyhardware, software and/or firmware required to implement it (such as,e.g., network routers, etc.). For example, communications network 1104may include an 802.11, 802.16, 802.20, and/or WiMax network. Thecommunications network 1104 may include a public network, such as theInternet, a private network, such as an intranet, or combinationsthereof, and may utilize a variety of networking protocols now availableor later developed including, but not limited to TCP/IP based networkingprotocols. The computing device 1102 and control system 1101 may beembodied by one or more computing systems, such as system 1200 describedwith reference to FIG. 12 .

The computing device 1102 and control system 1101 can be configured toperform operations comprising scanning the beam across a scannablesurface of a target along a first path; and scanning the beam across thescannable surface of the target along a second path, wherein the firstpath forms a first pattern at a first radial orientation, and the secondpath forms substantially the first pattern at a second radialorientation different from the first radial orientation. The beam ispulsed while scanning along the first and second paths. The beamcontinuously propagates while scanning along the first and second paths.The beam moves from an inner region to an outer region of the scannablesurface and back to the inner region in the first pattern. The beammoves from an outer region to an inner region of the scannable surfaceand back to the outer region in the first pattern. The first patterncomprises a spiral and a mirror image of the spiral. The first patternhas a first half and a second half, wherein the first and second halvesare symmetrical. The first pattern is continuously curved. The firstpattern has a start location and a stop location, wherein the startlocation is at or adjacent to the stop location. The first radialorientation differs from the second radial orientation by 180 degrees.The operations further comprising: scanning the beam across thescannable surface of the target along a third path, wherein the thirdpath forms the first pattern at a third radial orientation differentfrom the first and second radial orientations. The first, second, andthird radial orientations differ by 120 degrees. The operations furthercomprising: scanning the beam across the scannable surface of the targetalong a fourth path, wherein the fourth path forms the first pattern ata fourth radial orientation different from the first, second, and thirdradial orientations. The first, second, third, and fourth radialorientations differ by 90 degrees. The operations further comprising:scanning the beam across the scannable surface of the target along afifth path, wherein the fifth path forms the first pattern at a fifthradial orientation different from the first, second, third, and fourthradial orientations. The first, second, third, fourth, and fifth radialorientations differ by 72 degrees. The first path corresponds to a firstinstance of a cycle, and the second path corresponds to a secondinstance of the cycle. In some implementations, scanning of the firstinstance of the cycle and the second instance of the cycle forms aclosed loop. The beam is a proton beam. The scannable surface is alithium or beryllium surface. The target generates neutrons whenscanned. The beam has a circular cross-sectional profile. The beam hasan elliptical cross-sectional profile. The beam has an annularcross-sectional profile. The beam has a hollow cross-sectional profile.The operations performing a boron neutron capture therapy (BNCT). Thebeam is generated by a beam system comprising: an ion source; a firstbeamline coupled with the ion source; a tandem accelerator coupled withthe first beamline; a second beamline coupled with the tandemaccelerator; and the target coupled with the second beamline. Thepattern exposes a majority of the scannable surface to the beam. Thesecond path forms the first pattern at the second radial orientationdifferent from the first radial orientation.

The computing device 1102 and control system 1101 can be configured toperform operations comprising scanning the beam across a scannablesurface of a target along a first path; and scanning the beam across thescannable surface of the target along a second path, wherein the firstpath forms a first pattern at a first radial orientation, and the secondpath forms a second pattern at a second radial orientation differentfrom the first radial orientation, wherein the first and second patternsare substantially the same but for the different radial orientations.The first and second patterns are the same but for the different radialorientations.

The computing device 1102 and control system 1101 can be configured toperform operations comprising establishing, using a computer processingsystem, a plurality of possible raster profiles for scanning the protonbeam across the target, each of the plurality of possible rasterprofiles comprising one or more beam parameters, each of the one or morebeam parameters characterizing a property of the proton beam and one ormore path parameters characterizing a path of the proton beam across thetarget; establishing, using the computer processing system, one or moretarget parameters characterizing the target; calculating, using thecomputer processing system, a value of a figure of merit for each of thepossible beam raster profiles, wherein the figure of merit is based on athermal loading of the target by the proton beam for the correspondingpossible raster profile; selecting, using the computer processingsystem, a raster profile from among the plurality of plurality ofpossible raster profiles based on the value of the figure of merit; anddirecting the proton beam across the target according to the selectedraster profile. Calculating the values for the figure of meritcomprises, for each of the possible raster profiles, calculating athermal load at each of a plurality of discrete portions of the targetbased on a linear relationship between the thermal load and a protonflux at each discrete portion for the corresponding raster profile. Eachdiscrete portion corresponds to an area of a surface of the target inthe path of the proton beam that is smaller than a dimension of theproton beam. The thermal load at each discrete portion is calculatedbased on heat transfer through a depth of the target away from a surfaceof the target on which the proton beam is incident. The figure of meritis selected from the group consisting of: a peak temperature of thetarget, a temperature change of the target, an average temperature ofthe target, and a usage efficiency of the target. The one or more beamparameters are selected from the group consisting of: a beam dimension,a beam shape, and a beam structure. The beam dimension is in a rangefrom 10 mm to 30 mm. The beam shape is circular or elliptical. Astructure of the beam is circular or annular. The one or more pathparameters is selected from the group consisting of: a frequencyassociated with the path of the proton beam, a linear velocity of theproton beam across a surface of the target, a number of radial scanlayers in a super cycle of the path of the proton beam, and a number ofsuper cycles of the path of the proton beam. The one or more targetparameters are selected from the group consisting of: target surfacearea, target thickness, and target composition. The target comprises alayer of lithium or a layer of beryllium. The target comprises a layerof a metal supporting the layer of lithium or the layer of beryllium.Selecting comprises presenting an operator of the proton beam with alist of the possible raster profiles and receiving, via the computersystem, a selection from the list by the operator. The operationsfurther comprising measuring one or more properties of the target andselecting the raster profile based on the measured property of thetarget. The one or more properties of the target comprise a temperatureof the target at one or more locations on the target. The operations,further comprising measuring one or more properties of the beam andselecting the raster profile based on the measured property of the beam.The one or more properties of the beam are measured upstream from thetarget. The selected raster profile defines a path for the proton beamhaving a minimum delay between successive exposures of a single locationof the target to the proton beam exceeds a threshold period. Theselected raster profile defines a path based on a trochoid shape. Thetrochoid shape comprises a plurality of lobes. The angular frequency ofthe proton beam varies for different lobes of the trochoid shape. Theselected raster profile comprises a varying angular velocity of theproton beam across the target surface. The selected raster profilecomprises a varying linear velocity of the proton beam across the targetsurface.

The computing device 1102 and control system 1101 can be configured toperform operations comprising monitoring a temperature of a target whilescanning a proton beam across a surface of the target according to afirst raster profile; and based on the monitored temperature, changingthe scanning from the first raster profile to a second raster profile,wherein the second raster profile and the first raster profile result indiffering heating profiles of the target according to a computer modelof a thermal loading of the target by the first and second rasterprofiles. The scanning is changed in response to selection of the secondraster profile from among a plurality of raster profiles by a humanoperator of the proton beam. The scanning is changed automaticallyaccording to a feedback or feedforward algorithm. The temperature ismonitored at multiple discrete locations of the target. The temperatureis monitored by obtaining a thermal image of the target.

The computing device 1102 and control system 1101 can be configured toperform operations comprising scanning a charged particle beam across ascannable surface of a target in a super cycle, wherein the super cyclecomprises a plurality of cycles, each cycle of the plurality of cycleshaving the same shape and a different azimuthal orientation, wherein theplurality of cycles are concatenated together such that a path of thecharged particle beam traverses the plurality of cycles in a closedloop. The plurality of cycles comprises two cycles azimuthally offset by180 degrees from each other. The plurality of cycles comprises threecycles azimuthally offset by 120 degrees from each other. The pluralityof cycles comprises four cycles azimuthally offset by 90 degrees fromeach other.

Referring now to FIG. 12 , a schematic view of an example computingsystem 1200 is provided. The system 1200 can be used for the operationsdescribed in association with the implementations described herein. Forexample, the system 1200 may be included in any or all of the servercomponents discussed herein. The system 1200 includes a processor 1210,a memory 1220, a storage device 1230, and an input/output device 1240.Each of the components 1210, 1220, 1230, and 1240 are interconnectedusing a system bus 1250. The processor 1210 is capable of processinginstructions for execution within the system 1200. In oneimplementation, the processor 1210 is a single-threaded processor. Inanother implementation, the processor 1210 is a multi-threadedprocessor. The processor 1210 is capable of processing instructionsstored in the memory 1220 or on the storage device 1230 to displaygraphical information for a user interface on the input/output device1240.

The memory 1220 stores information within the system 1200. In oneimplementation, the memory 1220 is a computer-readable medium. In oneimplementation, the memory 1220 is a volatile memory unit. In anotherimplementation, the memory 1220 is a non-volatile memory unit. Thestorage device 1230 is capable of providing mass storage for the system1200. In one implementation, the storage device 1230 is acomputer-readable medium. In various different implementations, thestorage device 1230 may be a floppy disk device, a hard disk device, anoptical disk device, or a tape device. The input/output device 1240provides input/output operations for the system 1200. In oneimplementation, the input/output device 1240 includes a keyboard and/orpointing device. In another implementation, the input/output device 1240includes a display unit for displaying graphical user interfaces.

In some implementations, two components may both leverage use of thesame processor, network interface, storage medium, or the like toperform their associated functions, such that duplicate hardware is notrequired for each device. The use of the terms “device” and/or“circuitry” as used herein with respect to components of the apparatustherefore can encompass particular hardware configured with software toperform the functions associated with that particular device, asdescribed herein.

The terms “device” and/or “circuitry” should be understood broadly toinclude hardware, in some embodiments, device and/or circuitry may alsoinclude software for configuring the hardware. For example, in someembodiments, device and/or circuitry may include processing circuitry,storage media, network interfaces, input/output devices, and the like.In some implementations, other elements of the system 1200 may provideor supplement the functionality of a particular component(s).

In some embodiments, the processor 1210 (and/or co-processor or anyother processing circuitry assisting or otherwise associated with theprocessor) may be in communication with the memory 1220 via a bus forpassing information among components of the apparatus. The memory 1220may be non-transitory and may include, for example, one or more volatileand/or non-volatile memories. In other words, for example, the memory1220 may be an electronic storage device (e.g., a computer readablestorage medium). The memory 1220 may be configured to store information,data, content, applications, instructions, or the like, for enabling thesystem 1200 to carry out various functions in accordance with exampleembodiments of the present disclosure, as described with reference toFIGS. 1-11 .

The processor 1210 may be embodied in a number of different ways andmay, for example, include one or more processing devices configured toperform independently. Additionally or alternatively, the processor 1210may include one or more processors configured in tandem via a bus toenable independent execution of instructions, pipelining, and/ormultithreading. The use of the terms “processing device” and/or“processing circuitry” may be understood to include a single coreprocessor, a multi-core processor, multiple processors internal to theapparatus, and/or remote or “cloud” processors.

In some implementations, the processor 1210 may be configured to executeinstructions stored in the memory 1220 or otherwise accessible to theprocessor. Alternatively or additionally, the processor 1210 may beconfigured to execute hard-coded functionality. As such, whetherconfigured by hardware or software methods, or by a combination ofhardware with software, the processor may represent an entity (e.g.,physically embodied in circuitry) capable of performing operationsaccording to an embodiment of the present disclosure while configuredaccordingly. Alternatively, as another example, when the processor 1210is embodied as an executor of software instructions, the instructionsmay specifically configure the processor 1210 to perform the algorithmsand/or operations described herein when the instructions are executed.The instructions can include those necessary to determine a scanningprofile and scan a target, as described with reference to FIGS. 1-11 .

In some implementations, the system 1200 may include input/output device1260 that may, in turn, be in communication with processor 1210 toprovide output to the user and, in some embodiments, to receive inputfrom the user. The input/output device 1260 may include a user interfaceand may include a device display, such as a user device display, thatmay include a web user interface, a mobile application, a client device,or the like. In some embodiments, the input/output device 1260 may alsoinclude a keyboard, a mouse, a joystick, a touch screen, touch areas,soft keys, a microphone, a speaker, or other input/output mechanisms.The processor and/or user interface circuitry including the processormay be configured to control one or more functions of one or more userinterface elements through computer program instructions (e.g., softwareand/or firmware) stored on a memory accessible to the processor (e.g.,memory 1220, and/or the like).

The communications device or circuitry 1240 may be any means such as adevice or circuitry embodied in either hardware or a combination ofhardware and software that is configured to receive and/or transmit datafrom/to a network and/or any other device or circuitry in communicationwith the system 1200. The communications device or circuitry 1240 mayinclude, for example, a network interface for enabling communicationswith a wired or wireless communication network. For example, thecommunications device or circuitry 1240 may include one or more networkinterface cards, antennas, buses, switches, routers, modems, andsupporting hardware and/or software, or any other device suitable forenabling communications via a network. Additionally or alternatively,the communication interface may include the circuitry for interactingwith the antenna(s) to cause transmission of signals via the antenna(s)or to handle receipt of signals received via the antenna(s). The signalsmay be transmitted by the system 1200 using any of a number of wirelesspersonal area network (PAN) technologies, such as current and futureBluetooth standards (including Bluetooth and Bluetooth Low Energy(BLE)), infrared wireless (e.g., IrDA), FREC, ultra-wideband (UWB),induction wireless transmission, or the like. In addition, it should beunderstood that the signals may be transmitted using Wi-Fi, Near FieldCommunications (NFC), Worldwide Interoperability for Microwave Access(WiMAX), or other proximity-based communications protocols.

Any such computer program instructions and/or other type of code may beloaded onto a computer, processor, or other programmable apparatus'circuitry to produce a machine, such that the computer, processor, orother programmable circuitry that executes the code on the machinecreates the means for implementing various functions, including thosedescribed herein.

Embodiments of the present disclosure may be configured as systems,methods, mobile devices, backend network devices, and the like.Accordingly, embodiments may comprise various means including entirelyof hardware or any combination of software and hardware. Furthermore,embodiments may take the form of a computer program product on at leastone non-transitory computer-readable storage medium havingcomputer-readable program instructions (e.g., computer software)embodied in the storage medium. Any suitable computer-readable storagemedium may be utilized including non-transitory hard disks, CD-ROMs,flash memory, optical storage devices, or magnetic storage devices.

Processing circuitry in accordance with the present disclosure caninclude one or more processors, microprocessors, controllers, and/ormicrocontrollers, each of which can be a discrete chip or distributedamongst (and a portion of) a number of different chips. Processingcircuitry in accordance with the present disclosure can include adigital signal processor, which can be implemented in hardware and/orsoftware of the processing circuitry in accordance with the presentdisclosure. Processing circuitry in accordance with the presentdisclosure can be communicatively coupled with the other components ofthe figures herein. Processing circuitry in accordance with the presentdisclosure can execute software instructions stored on memory that causethe processing circuitry to take a host of different actions and controlthe other components in figures herein.

Memory in accordance with the present disclosure can be shared by one ormore of the various functional units, or can be distributed amongst twoor more of them (e.g., as separate memories present within differentchips). Memory can also be a separate chip of its own. Memory can benon-transitory, and can be volatile (e.g., RAM, etc.) and/ornon-volatile memory (e.g., ROM, flash memory, F-RAM, etc.).

Computer program instructions for carrying out operations in accordancewith the described subject matter may be written in any combination ofone or more programming languages and software platforms such as but notlimited to Python, Labview platform by National Instruments, Java,JavaScript, Smalltalk, C++, C#, Transact-SQL, XML, PHP or the like andconventional procedural programming languages, such as the “C”programming language or similar programming languages.

Various aspects of the present subject matter are set forth below, inreview of, and/or in supplementation to, the described embodiments, withthe emphasis here being on the interrelation and interchangeability ofthe following embodiments. In other words, an emphasis is on the factthat each feature of the embodiments can be combined with each and everyother feature unless explicitly stated otherwise or logicallyimplausible.

It should be noted that all features, elements, components, functions,and steps described with respect to any embodiment provided herein areintended to be freely combinable and substitutable with those from anyother embodiment. If a certain feature, element, component, function, orstep is described with respect to only one embodiment, then it should beunderstood that that feature, element, component, function, or step canbe used with every other embodiment described herein unless explicitlystated otherwise. This paragraph therefore serves as antecedent basisand written support for the introduction of claims, at any time, thatcombine features, elements, components, functions, and steps fromdifferent embodiments, or that substitute features, elements,components, functions, and steps from one embodiment with those ofanother, even if the following description does not explicitly state, ina particular instance, that such combinations or substitutions arepossible. It is explicitly acknowledged that express recitation of everypossible combination and substitution is overly burdensome, especiallygiven that the permissibility of each and every such combination andsubstitution will be readily recognized by those of ordinary skill inthe art.

To the extent the embodiments disclosed herein include or operate inassociation with memory, storage, and/or computer readable media, thenthat memory, storage, and/or computer readable media are non-transitory.Accordingly, to the extent that memory, storage, and/or computerreadable media are covered by one or more claims, then that memory,storage, and/or computer readable media is only non-transitory.

As used herein and in the appended claims, the singular forms “a,” “an,”and “the” include plural referents unless the context clearly dictatesotherwise.

While the embodiments are susceptible to various modifications andalternative forms, specific examples thereof have been shown in thedrawings and are herein described in detail. It should be understood,however, that these embodiments are not to be limited to the particularform disclosed, but to the contrary, these embodiments are to cover allmodifications, equivalents, and alternatives falling within the spiritof the disclosure. Furthermore, any features, functions, steps, orelements of the embodiments may be recited in or added to the claims, aswell as negative limitations that define the inventive scope of theclaims by features, functions, steps, or elements that are not withinthat scope.

What is claimed is:
 1. A computer-implemented method for selecting araster profile for scanning a proton beam across a target, the methodcomprising: establishing, using a computer processing system, aplurality of possible raster profiles for scanning the proton beamacross the target, each of the plurality of possible raster profilescomprising one or more beam parameters, each of the one or more beamparameters characterizing a property of the proton beam and one or morepath parameters characterizing a path of the proton beam across thetarget; establishing, using the computer processing system, one or moretarget parameters characterizing the target; calculating, using thecomputer processing system, a value of a figure of merit for each of theplurality of possible raster profiles, wherein the figure of merit isbased on a thermal loading of the target by the proton beam for arespective possible raster profile of the plurality of possible rasterprofiles; and selecting, using the computer processing system, theraster profile from among the plurality of possible raster profilesbased on the value of the figure of merit.
 2. The computer-implementedmethod of claim 1, wherein calculating the values for the figure ofmerit comprises, for each of the plurality of possible raster profiles,calculating a thermal load at each of a plurality of discrete portionsof the target based on a linear relationship between the thermal loadand a proton flux at each discrete portion for the respective possibleraster profile.
 3. The computer-implemented method of claim 2, whereineach discrete portion corresponds to an area of a surface of the targetin the path of the proton beam that is smaller than a dimension of theproton beam.
 4. The computer-implemented method of claim 3, wherein thethermal load at each discrete portion is calculated based on heattransfer through a depth of the target away from a surface of the targeton which the proton beam is incident.
 5. The computer-implemented methodof claim 1, wherein the figure of merit is selected from the groupconsisting of: a peak temperature of the target, a temperature change ofthe target, an average temperature of the target, and a usage efficiencyof the target.
 6. The computer-implemented method of claim 1, whereinthe one or more beam parameters is selected from the group consistingof: a beam dimension, a beam shape, and a beam structure.
 7. Thecomputer-implemented method of claim 6, wherein selecting the rasterprofile from among the plurality of possible raster profiles based onthe value of the figure of merit comprises selecting a masked profileconfigured to avoid one or more portions of the target.
 8. Thecomputer-implemented method of claim 6, wherein the beam dimension is ina range from 10 mm to 30 mm.
 9. The computer-implemented method of claim6, wherein the beam shape is circular or elliptical and a structure ofthe proton beam is circular or annular.
 10. The computer-implementedmethod of claim 1, wherein the one or more path parameters is selectedfrom the group consisting of: a frequency associated with the path ofthe proton beam, a linear velocity of the proton beam across a surfaceof the target, a number of radial scan layers in a super cycle of thepath of the proton beam, and a number of super cycles of the path of theproton beam.
 11. The computer-implemented method of claim 1, wherein theone or more target parameters are selected from the group consisting of:a target surface area, a target thickness, and a target composition. 12.The computer-implemented method of claim 1, wherein the target comprisesa layer of lithium or a layer of beryllium.
 13. The computer-implementedmethod of claim 12, wherein the target comprises a layer of a metalsupporting the layer of lithium or the layer of beryllium.
 14. Thecomputer-implemented method of claim 1, wherein selecting comprisingpresenting an operator of the proton beam with a list of the pluralityof possible raster profiles and receiving, via the computer processingsystem, a selection from the list by the operator.
 15. Thecomputer-implemented method of claim 1, further comprising measuring oneor more properties of the target and selecting the raster profile basedon the one or more properties of the target.
 16. Thecomputer-implemented method of claim 15, wherein the one or moreproperties of the target comprises a temperature of the target at one ormore locations on the target.
 17. The computer-implemented method ofclaim 1, further comprising measuring one or more properties of theproton beam and selecting the raster profile based on the one or moreproperties of the proton beam.
 18. The computer-implemented method ofclaim 17, wherein the one or more properties of the proton beam aremeasured upstream from the target.
 19. The computer-implemented methodof claim 1, wherein the selected raster profile defines a path for theproton beam having a minimum delay between successive exposures of asingle location of the target to the proton beam exceeds a thresholdperiod.
 20. The computer-implemented method of claim 19, wherein theselected raster profile defines a path based on a trochoid shape. 21.The computer-implemented method of claim 20, wherein the trochoid shapecomprises a plurality of lobes.
 22. The computer-implemented method ofclaim 21, wherein an angular frequency of the proton beam varies fordifferent lobes of the trochoid shape.
 23. The computer-implementedmethod of claim 1, wherein the selected raster profile comprises avarying angular velocity of the proton beam across a target surface. 24.The computer-implemented method of claim 1, wherein the selected rasterprofile comprises a varying linear velocity of the proton beam across atarget surface.
 25. A computer-implemented method comprising: monitoringa temperature of a target while scanning a proton beam across a surfaceof the target according to a first raster profile; and based on themonitored temperature, changing the scanning from the first rasterprofile to a second raster profile, wherein the second raster profileand the first raster profile result in differing heating profiles of thetarget according to a computer model of a thermal loading of the targetby the first and second raster profiles.
 26. The computer-implementedmethod of claim 25, wherein the scanning is changed in response toselection of the second raster profile from among a plurality of rasterprofiles by a human operator of the proton beam.
 27. Thecomputer-implemented method of claim 25, wherein the scanning is changedautomatically according to a feedback or feedforward algorithm.
 28. Thecomputer-implemented method of claim 25, wherein the temperature ismonitored at multiple discrete locations of the target.
 29. Thecomputer-implemented method of claim 25, wherein the temperature ismonitored by obtaining a thermal image of the target.